Data Model



The 3-D Global Spatial Data Model: Foundation of the Spatial Data Infrastructure

environment. The 3-D Global Spatial Data Model: Foundation of the Spatial Data Infrastructure offers a new model for handling digital spatial data, the global spatial data model or GSDM.

The GSDM

Excel Data Analysis: Modeling and Simulation

This book is written for the students and practitioners who are looking for a single introductory Excel-based resource that covers three essential business and analytical skills—Data Analysis

Spatial Data on the Web: Modeling and Management

, and personalized smart devices.

Spatial Data on the Web links these two research streams, focusing on the modeling and management of spatial data in distributed systems. Belussi and his coeditors have

Data Mining: Concepts, Models, Methods, and Algorithms

in the book, just in case, I suppose. If you'd like more specific data mining knowledge, look elsewhere.

User review
Survey, not how-to
The subtitle advertises `concepts, models, methods

Fuzzy Modeling Tools for Data Mining and Knowledge Discovery (The Morgan Kaufmann Series in Data Management Systems)

Fuzzy Modeling and Genetic Algorithms for Data Mining and Exploration is a handbook for analysts, engineers, and managers involved in developing data mining models in business and government

Beginning Relational Data Modeling, Second Edition

to capture the information needs of a business system in a relational database model, but don't know where to start, then this is the book for you.

Beginning Relational Data Modeling

Market Models: A Guide to Financial Data Analysis

Market Models provides an authoritative and up-to-date treatment of the use of market data to develop models for financial analysis. Written by a leading figure in the field of financial data

Spatial Data Modelling for 3D GIS

This book covers fundamental aspects of spatial data modelling specifically on the aspect of three-dimensional (3D) modelling and structuring. Realisation of ?true? 3D GIS spatial system needs

Principles of Modeling Uncertainties in Spatial Data and Spatial Analyses

foundations are therefore still developing and data quality and uncertainty modeling for spatial data and spatial analysis is an important branch of that theory. Principles of Modeling Uncertainties in Spatial

Earthquake Data in Engineering Seismology: Predictive Models, Data Management and Networks (Geotechnical, Geological and Earthquake Engineering)

.  The book is divided into three principal sections.  The first section includes recent developments in regional and global ground-motion predictive models.
It presents discussions


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